Alternatively-spliced lncRNA-PNUTS promotes HCC cell EMT via regulating ZEB1 expression.

BACKGROUND: Long non-coding RNAs have been implicated in various cancers as they regulate critical cellular processes such as proliferation, migration, invasion, and apoptosis in tumorous tissues. lncRNA-PNUTS is newly reported as an alternatively-spliced lncRNA from PNUTS pre-mRNA that promotes oncogenesis in breast cancer. However, whether LncRNA-PNUTS plays a role in other forms of cancers, such as liver cancer, remains unknown. METHOD: In the current study, we investigated the potential role of lncRNA-PNUTS in hepatocellular carcinoma (HCC). The levels of lncRNA-PNUTS in tumorous tissues obtained from HCC patients were measured. The potential impacts of lncPNUTS on metastasis and invasion were investigated through gain- or loss- of function experiments in cell models of liver cancers, as well as other cellular assays such as trans-well assays and wound-healing assays. RESULTS: Here, we report that lncPNUTS was upregulated in human HCC tissues. Loss- and gain-of-function experiments indicated lncPNUTS promoted metastasis and invasion. In addition, ZEB1, which is involved in the activation of epithelial-mesenchymal-transition (EMT), was identified as a downstream target of lncPNUTS. CONCLUSION: Our findings indicated lncPNUTS promotes HCC cancer cell metastasis and invasion via targeting ZEB1 to activate the EMT pathway, suggesting that lncPNUTS is a potential prognostic marker and therapeutic target for HCC patients.

PLIN2 promotes HCC cells proliferation by inhibiting the degradation of HIF1α.

PLIN2 has been found to be dysregulated in several human malignancies, which influences cancer progression. However, the roles of PLIN2 in regulating hepatocellular carcinoma (HCC) progression are still unclear. Here, we revealed that PLIN2 was frequently upregulated in HCC cells and tissues, and increased PLIN2 expression was associated with poor prognosis outcomes in HCC. In HCC cells, overexpressing PLIN2 promoted cell proliferation, PLIN2-deficiency inhibited cell vitality. Mechanistically, silencing of PLIN2 expression downregulated hypoxia inducible factor 1-α (HIF1α) expression and this downregulation in turn inhibited the targeting genes of HIF1α. Furthermore, we found that PLIN2 stabilized and retarded the degradation of the HIF1α through autophagy-lysosomal pathway by inhibiting AMPK/ULK1. Collectively, we clarified the carcinogenic role of PLIN2 in HCC and suggested a prognostic biomarker for diagnosis and clinical therapy in the future.

Identification and Characterization of Robust Hepatocellular Carcinoma Prognostic Subtypes Based on an Integrative Metabolite-Protein Interaction Network.

Metabolite-protein interactions (MPIs) play key roles in cancer metabolism. However, our current knowledge about MPIs in cancers remains limited due to the complexity of cancer cells. Herein, the authors construct an integrative MPI network and propose a MPI network based hepatocellular carcinoma (HCC) subtyping and mechanism exploration workflow. Based on the expressions of hub proteins on the MPI network, two prognosis-distinctive HCC subtypes are identified. Meanwhile, multiple interdependent features of the poor prognostic subtype are observed, including hypoxia, DNA hypermethylation of metabolic pathways, fatty acid accumulation, immune pathway up-regulation, and exhausted T-cell infiltration. Notably, the immune pathway up-regulation is probably induced by accumulated unsaturated fatty acids which are predicted to interact with multiple immune regulators like SRC and TGFB1. Moreover, based on tumor microenvironment compositions, the poor prognostic subtype is further divided into two sub-populations showing remarkable differences in metabolism. The subtyping shows a strong consistency across multiple HCC cohorts including early-stage HCC. Overall, the authors redefine robust HCC prognosis subtypes and identify potential MPIs linking metabolism to immune regulations, thus promoting understanding and clinical applications about HCC metabolism heterogeneity.

Low HOXC10 expression in liver cancer regulates proliferation via a mechanism involving miR-221 and the MAPK signaling pathway.

Homeodomain-containing gene 10 (HOXC10) is associated with the progression of a variety of different types of human cancer; however, the role of HOXC10 in liver cancer is not completely understood. The present study aimed to investigate the mechanisms underlying the effects of HOXC10 on liver cancer tumorigenesis. Quantitative PCR and western blotting were used to detect the expression patterns of HOXC10 in cancer and adjacent healthy tissues. EdU, Cell Counting Kit-8 and colony formation assays were used to determine the functions of HOXC10 in liver cancer cell lines. ENCORI, TargetScan and miRTarBase were used to identify microRNAs that target HOXC10. The verification of the interaction between HOXC10 and microRNA-221 was determined by a luciferase assay. Compared with adjacent non-cancerous tissues, the expression of HOXC10 was markedly decreased in liver cancer tissues. A HOXC10 small interfering (si)RNA significantly attenuated HOXC10 expression at the mRNA and protein levels, and enhanced cell proliferation compared with the siRNA-negative control group. In addition, the luciferase reporter assay indicated that microRNA-221 directly bound to the 3'-untranslated region of HOXC10, and interfered with the inhibitory effect of HOXC10 on proliferation. In addition, HOXC10 knockdown elevated the expression levels of mitogen-activated protein kinase signaling pathway markers compared with the siRNA-negative control group. Therefore, the results of the present study may aid with the development of novel therapeutic regimens and diagnostic markers of liver cancer.

Nomograms for predicting overall survival and cancer-specific survival in patients with surgically resected intrahepatic cholangiocarcinoma.

PURPOSE: To develop and validate nomograms for predicting overall survival (OS) and cancer-specific survival (CSS) in patients with surgically resected intrahepatic cholangiocarcinoma (ICC). PATIENTS AND METHODS: The nomograms were developed using a development cohort of 947 ICC patients after surgery selected from Surveillance, Epidemiology, and End Results database, and externally validated using a training cohort of 159 patients admitted at our institution. Nomograms for OS and CSS were established based on the independent prognostic factors identified by COX regression models and Fine and Grey's models, respectively. The performance of the nomograms was validated internally and externally by using the concordance index (c-index), and calibration plot, and compared with that of AJCC 8th edition TNM staging system by using c-index and decision curve analysis. RESULTS: Age, T stage, M stage, lymph node ratio (LNR) level and tumor grade were independent prognostic predictors for OS in ICC patients, while T stage, M stage, LNR level and tumor grade were independent prognostic predictors for CSS. Nomogram predicting OS was with a c-index of 0.751 on internal validation and 0.725 up to external validation, while nomogram for CSS was with a c-index of 0.736 on internal validation and 0.718 up to external validation. Calibration plots exhibited that the nomograms-predicted and actual OS/CSS probabilities were fitted well on both internal and external validation. Additionally, the nomograms exhibited superiority over AJCC 8th edition TNM staging system with higher c-indices and net benefit gains, in predicting OS and CSS in ICC patients after surgery. CONCLUSION: The constructed nomograms could predict OS and CSS with good performance, which could be served as an effective tool for prognostic evaluation and individual treatment strategies optimization in ICC patients after surgery in clinical practice.